Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already declare `readOnlyHint`, `openWorldHint`, `idempotentHint`, and `destructiveHint: false`, so the description does not need to restate safety. It adds genuinely valuable behavioral detail: graceful degradation when GLEIF/OpenFIGI are unavailable, explicit `unresolved` entries rather than omission, `figi_candidates` when a name maps to multiple instruments, and source labeling for every identifier. No contradiction with the annotations exists.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is front-loaded with relatable query examples and earning most of its content, but it is written as one dense, sprawling paragraph with long parentheticals and semicolon-chained clauses. It would be substantially easier to scan with paragraph breaks or bullets for supported types, input formats, and edge-case behavior, so structure and conciseness are only adequate, not excellent.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's complexity and the absence of an output schema, the description covers the important contextual ground well: accepted entity types, multiple input formats, cross-source behavior, candidate ambiguity, unresolved identifiers, and failure degradation. It does not fully spell out the shape of the return object or all possible top-level keys, but it provides enough for an agent to invoke the tool correctly and interpret common outcomes.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The input schema already describes both parameters at 100% coverage, but the description substantially extends the meaning of `value`. It gives concrete examples (AAPL, 0000320193, 'ozempic'), clarifies that for bonds the issuer must be passed exactly as printed, and warns against including trailing security-class words. This is exactly the kind of practical parameter guidance that cannot be inferred from the schema alone.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description states a specific verb and resource: 'resolve a user-spoken NAME to the canonical/official identifiers other tools require as input,' backed by concrete query examples. It also differentiates this tool from lookups like `entity_profile` by focusing on name-to-ID resolution and explicitly calling out arbitrary identifiers (ticker, CIK, LEI, RxCUI, FIGI). This is far from a tautology and leaves no doubt about what the tool does.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description gives a clear directive: 'Use FIRST whenever you have a name but need an ID,' and enumerates the two supported types ('company' and 'drug') with detailed scope for each. It does not explicitly name sibling tools that should be used instead in specific cases, nor does it state when to avoid this tool, so it stops short of a full when/when-not matrix.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.